Due to the limited bandwidth of transmission channels, there are a limited number of bits available for encoding image information, for example, associated with a video teleconference. Thus, there are many image encoding techniques available which encode the image information with as few bits as possible using compression techniques, while still maintaining the quality and intelligibility that are required for a given application.
Generally, to obtain a composite image from a plurality of individual images, hereinafter referred to as a "multi-image composite," the pixel values of the individual images are typically combined in a predetermined visual order. Generating a multi-image composite, however, becomes more difficult if one or more of the individual images is compressed, particularly if the resulting image must maintain the same format. Specifically, since image compression is serially dependent and of variable length, pixel boundaries are not readily apparent in a compressed image. In addition, since many encoding techniques exhibit intra-frame pixel dependencies, the pixel values must be modified when generating a multi-image composite to reflect the reordering of the pixels.
Typically, when combining one or more compressed images to form a multi-image composite, the individual images are initially decompressed into the pixel domain, before the pixel values are reordered to create the multi-image composite. Finally, the multi-image composite is compressed to form the final image. The more popular image compression techniques, such as JPEG and MPEG, typically perform three (3) steps to generate a compressed image, namely, (i) transformation, such as a discrete cosine transform (DCT); (ii) quantization; and (iii) run-length encoding (RLE). Likewise, to decompress images using these same image compression techniques, the inverse of the compression steps are performed by the receiver on the compressed image, namely, (i) run-length decode; (ii) dequantization; and (iii) inverse discreet cosine transform (IDCT). Thus, to create a multi-image composite from N images, using conventional techniques, requires N decompressions, pixel reordering and one compression.
As apparent from the above-described deficiencies with image composition techniques, a need exists for an improved method and apparatus for generating a composite image from a plurality of compressed images. A further need exists for a technique for generating a multi-image composite image from a plurality of compressed individual images, requiring a reduced number of computational steps. Yet another need exists for a technique for generating a multi-image composite image from a plurality of compressed individual images, which exhibits reduced latency for video processing and reduced storage requirements.